code: def retina_detection_module(body, num_filter, filter_in, name):
      assert num_filter % 4 == 0
      conv1 = conv_act_layer(
          body,
          name + "_conv1",
          num_filter // 2,
          kernel=(3, 3),
          pad=(1, 1),
          stride=(1, 1),
          act_type="relu",
          separable=False,
          filter_in=filter_in,
      )
      conv2 = conv_act_layer(
          conv1,
          name + "_conv2",
          num_filter // 2,
          kernel=(3, 3),
          pad=(1, 1),
          stride=(1, 1),
          act_type="relu",
          separable=False,
          filter_in=num_filter // 2,
      )
      conv3 = conv_act_layer(
          conv2,
          name + "_conv3",
          num_filter // 2,
          kernel=(3, 3),
          pad=(1, 1),
          stride=(1, 1),
          act_type="relu",
          separable=False,
          filter_in=num_filter // 2,
      )
      conv4 = conv2 + conv3
      body = mx.sym.concat(
          *[conv1, conv4], dim=1, name=name + "_concat"
      )
      if config.USE_DCN > 0:
          body = conv_deformable(
              body, num_filter=num_filter, name=name + "_concat_dcn"
          )
      return body
  
file_path: insightface/detection/retinaface/rcnn/symbol/symbol_common.py
imports: import mxnet
  import mxnet.ndarray
  import numpy
  from rcnn.config import config
  from rcnn.PY_OP import rpn_fpn_ohem3, cascade_refine
label_desc: Use image node_id 7 for calling a global function with example usage: retina_detection_module(body, num_filter, filter_in, name) and returns: body